Unlock transparency,
build AI responsibly
Powerful, self-serve AI-risk intelligence
for developers, end-users and regulators.
Next-generation AI-risk monitoring
integrated with multiple technology stacks
WHAT IS AI-RISK?
AI can & does go wrong
Any failure of AI-enabled automation in the regulated enterprise creates operational and compliance liability with novel, dynamic risks for both the data office and the three lines of defence. This necessitates risk monitoring of AI at scale.
AI Controls
Repository
Taxonomy of re-usable artefacts and internal controls libraries to ensure that your automated systems are within your risk appetite, while assuring policy compliance.
AI Risk
Observability
Single pane of glass for data scientists, developers and risk teams to collaborate across the automation value chain, enabling risk transparency and visibility.
AI Outcomes
Interpretability
Integrated explainability to demonstrate machine-learning risk provenance to executive stakeholders and regulators, fostering trust and accountability.
Are you AI ready?
Audit your readiness & discover newer, emerging risks in your AI-enabled product or service.
Sign up for a free AI-risk check list!
ACCELERATE
Turn AI-risk into Opportunity!
Gain 360° visibility and transparency into all your AI-risks with a comprehensive pre-built taxonomy.
Innovate with confidence & trust in your AI.
AI Use-Cases
Unique AI-risks
BENEFITS
See how it all comes together
With Zupervise, you can now analyse risks across multiple layers of AI: models, training data, inputs & outputs.
Step 1 - Analyse
Identify your AI Risk universe
Discover risks in your current business process design. Enable out of the box AI Risk Controls & manage a balance between AI risk appetite and automation experimentation.
Step 2 - Optimise
Unify AI Risk Data
Foster a culture of AI Risk mitigation and make intelligent & informed risk decisions from a single shared system of record. Govern AI Risks originating from the quality of historical data and that of evaluation & benchmark data-sets.
Step 3 - Govern
Gain Visibility into AI Risk Trends
Delineate accountability and make it easier to place trust in your AI investments with data-driven insights into emerging AI Risks. For each AI Risk, monitor multiple signals, including changes in attributes to be able to forecast a material effect on your risk appetite.
OUTCOMES
Streamline
AI-risk
Transparency
Identify AI-Risks
Build your own AI Risk and AI controls taxonomy, or re-use our artefacts, templates and libraries to develop forward-looking internal controls.
Breakdown Governance Silos
Single pane of glass dashboard that has source, risk and operational data integration capabilities to improve transparency in automation deployments & outcomes.
Demonstrate Regulatory Compliance
Articulate algorithmic risk provenance to executive stakeholders and regulators on-demand.
SOLUTIONS
Questions
we help
you answer
Discover diverse
implications of
AI Risks
Regulatory
Will your AI comply with proposed regulatory policies & legislation?
Cyber
Are your AI assets
secured against adversarial attacks?
Privacy
Does your AI process sensitive data for automated decisioning?
Third Party
Can you vet your AI technology vendor's deployments?
Conduct
How do humans in the loop interpret your AI's reasoning provenance?
ESG
Is your AI ethical, responsible and trustworthy?
INSPIRATION
Thought leadership,
news & industry updates
A collection of original content on AI Risk governance, curated news & research.
Let’s do this
Get started with
Zupervise
Book a demo with an AI-risk expert to see Zupervise in action.